Using OLR
vclust <- varclus (~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil + TC_weath_rock + TC_unstable_structure + T_construction + spring + landfill + garbage + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank + tree + ground_veg + deforestation + banana + drainage , data=train.data)
# took out density since training has 0 d4 and it was not allowing do the plot
p <- plot(vclust)
par(mfrow=c(6,5))
plot.xmean.ordinaly (risk~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil + TC_weath_rock + TC_unstable_structure + T_construction + spring + landfill + garbage + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank + tree + ground_veg + deforestation + banana + drainage, data=train.data, cr=TRUE , subn=FALSE)
#angle + building+density+EN +TC + TC_mature_Soil + TC_saprolito + TC_weath_rock + TC_rock + TC_geol_desfav + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + DepTaludeAterro + aterro + lixo + entulho + crack + belly_wall + scars + drawback + tilted + fracture + conc_rainfall_water + wastewater + leak + septic_tank + drainage + tree + ground_veg + deforestation + banana
Diagnostic 2: Proportion (-5% of one of the parameters based on what is expected. Since some parameters have 2 predictors, others 5)
#library(plyr)
brick <- count(train.data$brick) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "brick")
wood <- count(train.data$wood) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "wood")
mixed <- count(train.data$mixed) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "mixed")
TC_mature_soil <- count(train.data$TC_mature_soil) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_mature_soil")
T_construction <- count(train.data$T_construction ) %>%
mutate ("Percentage"=(freq/265)*100) %>%
mutate("Classifier" = "T_construction ")
spring <- count(train.data$spring) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "spring")
landfill <- count(train.data$landfill) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "landfill")
garbage <- count(train.data$garbage) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "garbage")
crack <- count(train.data$crack) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "crack")
leaning_wall <- count(train.data$leaning_wall) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "leaning_wall")
scars <- count(train.data$scars) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "DepTaludeAterro")
downward_floor <- count(train.data$downward_floor) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "scars")
tilted <- count(train.data$tilted) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "tilted")
conc_rainfall <- count(train.data$conc_rainfall) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "conc_rainfall")
wastewater <- count(train.data$wastewater) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "wastewater")
leak <- count(train.data$leak) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "conc_rainfall_water")
septic_tank <- count(train.data$septic_tank) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "septic_tank")
angle <- count(train.data$angle) # angle A less than 5% but the rest are okay (3,50, 91, 277, 109) Expected=106
angle <- angle %>%
mutate("Percentage"=(freq/106)*100)%>%
mutate("Classifier" = "angle")
EN <- count(train.data$EN) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "EN")
TC <- count(train.data$TC) %>%
mutate ("Percentage"=(freq/265)*100) %>%
mutate("Classifier" = "TC")
TC_saprolite_soil <- count(train.data$TC_saprolite_soil ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_saprolite_soil ")
banana <- count(train.data$banana) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "banana")
drainage <- count(train.data$drainage) %>%
mutate ("Percentage"=(freq/176.7)*100)%>%
mutate("Classifier" = "drainage")
deforestation <- count(train.data$deforestation) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "deforestation")
TC_unstable_structure <- count(train.data$TC_unstable_structure ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_unstable_structure ")
tree <- count(train.data$tree) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "tree")
ground_veg <- count(train.data$ground_veg) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "ground_veg")
density <- count(train.data$density) %>% #(79, 415, 36) # d4 =0
mutate ("Percentage"=(freq/132.5)*100)%>%
mutate("Classifier" = "density")
TC_weath_rock <- count(train.data$TC_weath_rock ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_weath_rock ")
fracture <- count(train.data$fracture) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "fracture")
df <- rbind(brick, wood, mixed, TC_mature_soil, T_construction, spring, landfill, garbage, crack, leaning_wall, scars, downward_floor, tilted, conc_rainfall, wastewater, leak, septic_tank, angle, EN, TC, TC_saprolite_soil, banana, drainage, deforestation, TC_unstable_structure, tree, ground_veg,density, TC_weath_rock, fracture)
df
## x freq Percentage Classifier
## 1 FALSE 38 14.3396226 brick
## 2 TRUE 492 185.6603774 brick
## 3 FALSE 456 172.0754717 wood
## 4 TRUE 74 27.9245283 wood
## 5 FALSE 492 185.6603774 mixed
## 6 TRUE 38 14.3396226 mixed
## 7 FALSE 258 97.3584906 TC_mature_soil
## 8 TRUE 272 102.6415094 TC_mature_soil
## 9 FALSE 204 76.9811321 T_construction
## 10 TRUE 326 123.0188679 T_construction
## 11 FALSE 511 192.8301887 spring
## 12 TRUE 19 7.1698113 spring
## 13 FALSE 329 124.1509434 landfill
## 14 TRUE 201 75.8490566 landfill
## 15 FALSE 346 130.5660377 garbage
## 16 TRUE 184 69.4339623 garbage
## 17 FALSE 448 169.0566038 crack
## 18 TRUE 82 30.9433962 crack
## 19 FALSE 500 188.6792453 leaning_wall
## 20 TRUE 30 11.3207547 leaning_wall
## 21 FALSE 317 119.6226415 DepTaludeAterro
## 22 TRUE 213 80.3773585 DepTaludeAterro
## 23 FALSE 467 176.2264151 scars
## 24 TRUE 63 23.7735849 scars
## 25 FALSE 425 160.3773585 tilted
## 26 TRUE 105 39.6226415 tilted
## 27 FALSE 19 7.1698113 conc_rainfall
## 28 TRUE 511 192.8301887 conc_rainfall
## 29 FALSE 210 79.2452830 wastewater
## 30 TRUE 320 120.7547170 wastewater
## 31 FALSE 333 125.6603774 conc_rainfall_water
## 32 TRUE 197 74.3396226 conc_rainfall_water
## 33 FALSE 528 199.2452830 septic_tank
## 34 TRUE 2 0.7547170 septic_tank
## 35 C 29 27.3584906 angle
## 36 D 128 120.7547170 angle
## 37 E 373 351.8867925 angle
## 38 FALSE 340 128.3018868 EN
## 39 TRUE 190 71.6981132 EN
## 40 FALSE 26 9.8113208 TC
## 41 TRUE 504 190.1886792 TC
## 42 FALSE 449 169.4339623 TC_saprolite_soil
## 43 TRUE 81 30.5660377 TC_saprolite_soil
## 44 FALSE 343 129.4339623 banana
## 45 TRUE 187 70.5660377 banana
## 46 Y 67 37.9173741 drainage
## 47 P 233 131.8619128 drainage
## 48 N 230 130.1641200 drainage
## 49 FALSE 495 186.7924528 deforestation
## 50 TRUE 35 13.2075472 deforestation
## 51 FALSE 519 195.8490566 TC_unstable_structure
## 52 TRUE 11 4.1509434 TC_unstable_structure
## 53 FALSE 210 79.2452830 tree
## 54 TRUE 320 120.7547170 tree
## 55 FALSE 154 58.1132075 ground_veg
## 56 TRUE 376 141.8867925 ground_veg
## 57 d1 66 49.8113208 density
## 58 d2 430 324.5283019 density
## 59 d3 34 25.6603774 density
## 60 FALSE 518 195.4716981 TC_weath_rock
## 61 TRUE 12 4.5283019 TC_weath_rock
## 62 FALSE 529 199.6226415 fracture
## 63 TRUE 1 0.3773585 fracture
TC_weath_rock, TC_rock_TC_geol_desf, fracture, TC_rock
f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana , data=train.data, x=TRUE , y=TRUE)
f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana + septic_tank +TC_mature_Soil , data=train.data, x=TRUE , y=TRUE) print (f1 , latex =TRUE , coefs =5) stargazer(anova(f1), type=“text”, style=“default”)
# Equation 1
eq_OLR_01 <- polr(risk ~ brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_01))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -1.05496407 0.4555914 -2.3155925 1.029026e-02
## woodTRUE 1.28505800 0.3328812 3.8604108 5.659828e-05
## ENTRUE 0.67550471 0.3697407 1.8269685 3.385225e-02
## TC_mature_soilTRUE 0.45968566 0.2206572 2.0832571 1.861390e-02
## T_constructionTRUE 0.25183255 0.3618443 0.6959693 2.432240e-01
## springTRUE 0.45300279 0.6186059 0.7322962 2.319939e-01
## landfillTRUE 0.16690916 0.3234762 0.5159859 3.029321e-01
## leakTRUE -0.05218241 0.2355406 -0.2215431 4.123348e-01
## garbageTRUE 0.21242666 0.2902545 0.7318635 2.321259e-01
## crackTRUE 1.71380934 0.3291884 5.2061651 9.639157e-08
## leaning_wallTRUE 2.32910641 0.5388099 4.3226870 7.707015e-06
## scarsTRUE 3.97101508 0.3565513 11.1372899 4.129726e-29
## downward_floorTRUE 0.81769676 0.3675403 2.2247809 1.304797e-02
## tiltedTRUE 1.28849743 0.3169039 4.0658933 2.392441e-05
## septic_tankTRUE -1.57300635 1.4252846 -1.1036437 1.348739e-01
## conc_rainfallTRUE 1.58976162 0.5307732 2.9951807 1.371411e-03
## wastewaterTRUE 0.68386836 0.2375188 2.8792183 1.993311e-03
## ground_vegTRUE 0.76923552 0.2556269 3.0092117 1.309633e-03
## angleD 0.06851177 0.4882918 0.1403091 4.442079e-01
## angleE 0.40650978 0.5528044 0.7353591 2.310604e-01
## TC_saprolite_soilTRUE 0.43432233 0.2945352 1.4746025 7.015972e-02
## R1|R2 0.35640040 0.8692838 0.4099931 3.409055e-01
## R2|R3 4.68198705 0.9145671 5.1193479 1.532969e-07
## R3|R4 9.80698857 1.0074561 9.7344081 1.075330e-22
stargazer((ctable), type="text", style="default", digits = 2)
##
## ======================================================
## Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE -1.05 0.46 -2.32 0.01
## woodTRUE 1.29 0.33 3.86 0.0001
## ENTRUE 0.68 0.37 1.83 0.03
## TC_mature_soilTRUE 0.46 0.22 2.08 0.02
## T_constructionTRUE 0.25 0.36 0.70 0.24
## springTRUE 0.45 0.62 0.73 0.23
## landfillTRUE 0.17 0.32 0.52 0.30
## leakTRUE -0.05 0.24 -0.22 0.41
## garbageTRUE 0.21 0.29 0.73 0.23
## crackTRUE 1.71 0.33 5.21 0.0000
## leaning_wallTRUE 2.33 0.54 4.32 0.0000
## scarsTRUE 3.97 0.36 11.14 0
## downward_floorTRUE 0.82 0.37 2.22 0.01
## tiltedTRUE 1.29 0.32 4.07 0.0000
## septic_tankTRUE -1.57 1.43 -1.10 0.13
## conc_rainfallTRUE 1.59 0.53 3.00 0.001
## wastewaterTRUE 0.68 0.24 2.88 0.002
## ground_vegTRUE 0.77 0.26 3.01 0.001
## angleD 0.07 0.49 0.14 0.44
## angleE 0.41 0.55 0.74 0.23
## TC_saprolite_soilTRUE 0.43 0.29 1.47 0.07
## R1| R2 0.36 0.87 0.41 0.34
## R2| R3 4.68 0.91 5.12 0.0000
## R3| R4 9.81 1.01 9.73 0
## ------------------------------------------------------
less p-value = 0.10 (TC_saprolitoTRUE,TaterroTRUE, DepTaludeAterroTRUE,DepTaludeAterroTRUE,landfillTRUE, construction_depositTRUE, leakTRUE)
par(mfrow=c(5,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
,data=train.data, cr=TRUE , subn=FALSE , cex.lab=1.5, cex.axis=2, cex.sub=2, cex.main=2)
Equation 1
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +-----------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +-----------------+---+---+----+----------+------------+----------+
## |brick |No | 38|Inf | 2.8903718| 1.673976434|-0.4274440|
## | |Yes|491|Inf | 2.2936565|-0.110090690|-2.1119270|
## +-----------------+---+---+----+----------+------------+----------+
## |wood |No |455|Inf | 2.2344036|-0.207332945|-2.3122939|
## | |Yes| 74|Inf | 3.1640676| 1.455287233|-0.5543107|
## +-----------------+---+---+----+----------+------------+----------+
## |EN |No |339|Inf | 1.8769173|-0.499827870|-2.3321439|
## | |Yes|190|Inf | 4.5432948| 0.923670839|-1.3862944|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_mature_soil |No |258|Inf | 1.9547991|-0.202236866|-2.1465808|
## | |Yes|271|Inf | 2.8371272| 0.185027918|-1.7245072|
## +-----------------+---+---+----+----------+------------+----------+
## |T_construction |No |204|Inf | 1.5404450|-0.996613121|-3.0757750|
## | |Yes|325|Inf | 3.3514977| 0.588744061|-1.5059589|
## +-----------------+---+---+----+----------+------------+----------+
## |spring |No |510|Inf | 2.2875795|-0.031375123|-2.0532392|
## | |Yes| 19|Inf | Inf| 0.773189888| 0.1053605|
## +-----------------+---+---+----+----------+------------+----------+
## |landfill |No |328|Inf | 1.8647846|-0.523855124|-2.4523305|
## | |Yes|201|Inf | 4.1896547| 0.878289614|-1.3312346|
## +-----------------+---+---+----+----------+------------+----------+
## |leak |No |332|Inf | 1.9322113|-0.390427231|-2.3848232|
## | |Yes|197|Inf | 3.6480575| 0.662841831|-1.3673664|
## +-----------------+---+---+----+----------+------------+----------+
## |garbage |No |346|Inf | 2.0632861|-0.279257423|-2.4298469|
## | |Yes|183|Inf | 3.0853444| 0.525424423|-1.2739652|
## +-----------------+---+---+----+----------+------------+----------+
## |crack |No |447|Inf | 2.1897896|-0.292904016|-2.5625426|
## | |Yes| 82|Inf | 3.6888795| 2.093234864|-0.2451225|
## +-----------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |499|Inf | 2.2635346|-0.108322227|-2.1300270|
## | |Yes| 30|Inf | Inf| 2.639057330| 0.0000000|
## +-----------------+---+---+----+----------+------------+----------+
## |scars |No |316|Inf | 1.7697806|-1.450832882|-4.6475909|
## | |Yes|213|Inf | 5.3565863| 3.120895417|-0.8228250|
## +-----------------+---+---+----+----------+------------+----------+
## |downward_floor |No |466|Inf | 2.1877233|-0.267681406|-2.2116133|
## | |Yes| 63|Inf | Inf| 4.127134385|-0.6225296|
## +-----------------+---+---+----+----------+------------+----------+
## |tilted |No |424|Inf | 2.1062528|-0.431082272|-2.6115899|
## | |Yes|105|Inf | 4.6443909| 2.495269437|-0.5260931|
## +-----------------+---+---+----+----------+------------+----------+
## |septic_tank |No |527|Inf | 2.3236385| 0.003795071|-1.9095425|
## | |Yes| 2|Inf | Inf| -Inf| -Inf|
## +-----------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 19|Inf |-0.3184537|-2.890371758| -Inf|
## | |Yes|510|Inf | 2.5776884| 0.062765696|-1.8718022|
## +-----------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.505749471|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.322516025|-1.5252932|
## +-----------------+---+---+----+----------+------------+----------+
## |ground_veg |No |154|Inf | 1.3781972|-1.261131218|-2.6672282|
## | |Yes|375|Inf | 3.1107337| 0.461345567|-1.6984588|
## +-----------------+---+---+----+----------+------------+----------+
## |angle |C | 29|Inf | Inf|-0.068992871|-3.3322045|
## | |D |128|Inf | 3.4339872| 0.899941594|-1.3192837|
## | |E |372|Inf | 2.0348576|-0.292387963|-2.1162555|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_saprolite_soil|No |448|Inf | 2.2172252|-0.062520357|-2.0521106|
## | |Yes| 81|Inf | 3.2580965| 0.323787077|-1.3256697|
## +-----------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +-----------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=1, cex.sub=1)
f2 <- lrm(risk ~ angle + building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + drainage + TC_mature_Soil + density + TC + tree +ground_veg + deforestation + banana , data=train.data, x=TRUE , y=TRUE)
stargazer(anova(f2), type="text", style="default")
eq_OLR_02 <- polr(risk ~ brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,
data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_02))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -0.99839616 0.5428311 -1.8392391 3.294001e-02
## woodTRUE 1.10993097 0.3529454 3.1447663 8.310977e-04
## ENTRUE 0.72722501 0.4012787 1.8122690 3.497232e-02
## TC_mature_soilTRUE 0.33486733 0.2337239 1.4327474 7.596502e-02
## T_constructionTRUE 0.34837533 0.3687639 0.9447110 1.724032e-01
## landfillTRUE 0.04192925 0.3282625 0.1277308 4.491810e-01
## leakTRUE -0.15834896 0.2411727 -0.6565791 2.557258e-01
## garbageTRUE 0.23285067 0.2972795 0.7832720 2.167337e-01
## crackTRUE 1.85510225 0.3359040 5.5227162 1.668994e-08
## leaning_wallTRUE 2.27191766 0.5334917 4.2585808 1.028645e-05
## treeTRUE -0.10955413 0.2503265 -0.4376450 3.308218e-01
## downward_floorTRUE 0.82812669 0.3670432 2.2562107 1.202872e-02
## tiltedTRUE 1.25186506 0.3181684 3.9345990 4.166785e-05
## ground_vegTRUE 0.67407659 0.2776482 2.4278085 7.595180e-03
## scarsTRUE 3.90493338 0.3568373 10.9431755 3.582282e-28
## mixedTRUE -0.01365161 0.5350762 -0.0255134 4.898227e-01
## conc_rainfallTRUE 1.09569988 0.5699712 1.9223777 2.727913e-02
## wastewaterTRUE 0.46772797 0.2457800 1.9030349 2.851799e-02
## angleD -0.11780506 0.4906140 -0.2401176 4.051195e-01
## angleE 0.33276495 0.5611384 0.5930176 2.765847e-01
## bananaTRUE 0.27019701 0.2596494 1.0406224 1.490254e-01
## drainage.L 0.96971595 0.2903259 3.3400943 4.187497e-04
## drainage.Q -0.20313331 0.1911265 -1.0628211 1.439315e-01
## TC_saprolite_soilTRUE 0.42014178 0.3008052 1.3967240 8.124829e-02
## TCTRUE 0.44251685 0.5498729 0.8047620 2.104785e-01
## deforestationTRUE 0.51591624 0.4231407 1.2192547 1.113738e-01
## R1|R2 0.12299067 1.1444994 0.1074624 4.572111e-01
## R2|R3 4.62692869 1.1644256 3.9735717 3.540142e-05
## R3|R4 9.73403071 1.2522017 7.7735327 3.816348e-15
stargazer((ctable), type="text", style="default", digits=2)
##
## ======================================================
## Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE -1.00 0.54 -1.84 0.03
## woodTRUE 1.11 0.35 3.14 0.001
## ENTRUE 0.73 0.40 1.81 0.03
## TC_mature_soilTRUE 0.33 0.23 1.43 0.08
## T_constructionTRUE 0.35 0.37 0.94 0.17
## landfillTRUE 0.04 0.33 0.13 0.45
## leakTRUE -0.16 0.24 -0.66 0.26
## garbageTRUE 0.23 0.30 0.78 0.22
## crackTRUE 1.86 0.34 5.52 0.0000
## leaning_wallTRUE 2.27 0.53 4.26 0.0000
## treeTRUE -0.11 0.25 -0.44 0.33
## downward_floorTRUE 0.83 0.37 2.26 0.01
## tiltedTRUE 1.25 0.32 3.93 0.0000
## ground_vegTRUE 0.67 0.28 2.43 0.01
## scarsTRUE 3.90 0.36 10.94 0
## mixedTRUE -0.01 0.54 -0.03 0.49
## conc_rainfallTRUE 1.10 0.57 1.92 0.03
## wastewaterTRUE 0.47 0.25 1.90 0.03
## angleD -0.12 0.49 -0.24 0.41
## angleE 0.33 0.56 0.59 0.28
## bananaTRUE 0.27 0.26 1.04 0.15
## drainage.L 0.97 0.29 3.34 0.0004
## drainage.Q -0.20 0.19 -1.06 0.14
## TC_saprolite_soilTRUE 0.42 0.30 1.40 0.08
## TCTRUE 0.44 0.55 0.80 0.21
## deforestationTRUE 0.52 0.42 1.22 0.11
## R1| R2 0.12 1.14 0.11 0.46
## R2| R3 4.63 1.16 3.97 0.0000
## R3| R4 9.73 1.25 7.77 0
## ------------------------------------------------------
par(mfrow=c(6,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation
,data=train.data, cr=TRUE , subn=FALSE , cex.lab=1.5, cex.axis=4, cex.sub=4, cex.main=4)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,data=train.data
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +-----------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +-----------------+---+---+----+----------+------------+----------+
## |brick |No | 38|Inf | 2.8903718| 1.673976434|-0.4274440|
## | |Yes|491|Inf | 2.2936565|-0.110090690|-2.1119270|
## +-----------------+---+---+----+----------+------------+----------+
## |wood |No |455|Inf | 2.2344036|-0.207332945|-2.3122939|
## | |Yes| 74|Inf | 3.1640676| 1.455287233|-0.5543107|
## +-----------------+---+---+----+----------+------------+----------+
## |EN |No |339|Inf | 1.8769173|-0.499827870|-2.3321439|
## | |Yes|190|Inf | 4.5432948| 0.923670839|-1.3862944|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_mature_soil |No |258|Inf | 1.9547991|-0.202236866|-2.1465808|
## | |Yes|271|Inf | 2.8371272| 0.185027918|-1.7245072|
## +-----------------+---+---+----+----------+------------+----------+
## |T_construction |No |204|Inf | 1.5404450|-0.996613121|-3.0757750|
## | |Yes|325|Inf | 3.3514977| 0.588744061|-1.5059589|
## +-----------------+---+---+----+----------+------------+----------+
## |landfill |No |328|Inf | 1.8647846|-0.523855124|-2.4523305|
## | |Yes|201|Inf | 4.1896547| 0.878289614|-1.3312346|
## +-----------------+---+---+----+----------+------------+----------+
## |leak |No |332|Inf | 1.9322113|-0.390427231|-2.3848232|
## | |Yes|197|Inf | 3.6480575| 0.662841831|-1.3673664|
## +-----------------+---+---+----+----------+------------+----------+
## |garbage |No |346|Inf | 2.0632861|-0.279257423|-2.4298469|
## | |Yes|183|Inf | 3.0853444| 0.525424423|-1.2739652|
## +-----------------+---+---+----+----------+------------+----------+
## |crack |No |447|Inf | 2.1897896|-0.292904016|-2.5625426|
## | |Yes| 82|Inf | 3.6888795| 2.093234864|-0.2451225|
## +-----------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |499|Inf | 2.2635346|-0.108322227|-2.1300270|
## | |Yes| 30|Inf | Inf| 2.639057330| 0.0000000|
## +-----------------+---+---+----+----------+------------+----------+
## |tree |No |209|Inf | 1.7104138|-0.601209685|-2.2460147|
## | |Yes|320|Inf | 3.0122616| 0.379489622|-1.7346011|
## +-----------------+---+---+----+----------+------------+----------+
## |downward_floor |No |466|Inf | 2.1877233|-0.267681406|-2.2116133|
## | |Yes| 63|Inf | Inf| 4.127134385|-0.6225296|
## +-----------------+---+---+----+----------+------------+----------+
## |tilted |No |424|Inf | 2.1062528|-0.431082272|-2.6115899|
## | |Yes|105|Inf | 4.6443909| 2.495269437|-0.5260931|
## +-----------------+---+---+----+----------+------------+----------+
## |ground_veg |No |154|Inf | 1.3781972|-1.261131218|-2.6672282|
## | |Yes|375|Inf | 3.1107337| 0.461345567|-1.6984588|
## +-----------------+---+---+----+----------+------------+----------+
## |scars |No |316|Inf | 1.7697806|-1.450832882|-4.6475909|
## | |Yes|213|Inf | 5.3565863| 3.120895417|-0.8228250|
## +-----------------+---+---+----+----------+------------+----------+
## |mixed |No |491|Inf | 2.2936565|-0.077431740|-2.0299933|
## | |Yes| 38|Inf | 2.8903718| 1.029619417|-0.8979416|
## +-----------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 19|Inf |-0.3184537|-2.890371758| -Inf|
## | |Yes|510|Inf | 2.5776884| 0.062765696|-1.8718022|
## +-----------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.505749471|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.322516025|-1.5252932|
## +-----------------+---+---+----+----------+------------+----------+
## |angle |C | 29|Inf | Inf|-0.068992871|-3.3322045|
## | |D |128|Inf | 3.4339872| 0.899941594|-1.3192837|
## | |E |372|Inf | 2.0348576|-0.292387963|-2.1162555|
## +-----------------+---+---+----+----------+------------+----------+
## |banana |No |342|Inf | 1.9129039|-0.366625275|-2.3058057|
## | |Yes|187|Inf | 4.1163235| 0.677146839|-1.3997174|
## +-----------------+---+---+----+----------+------------+----------+
## |drainage |Y | 67|Inf | 0.7156200|-1.998095902|-4.1896547|
## | |P |232|Inf | 2.4168532|-0.492476485|-2.5374247|
## | |N |230|Inf | 3.6198866| 0.996829594|-1.2809338|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_saprolite_soil|No |448|Inf | 2.2172252|-0.062520357|-2.0521106|
## | |Yes| 81|Inf | 3.2580965| 0.323787077|-1.3256697|
## +-----------------+---+---+----+----------+------------+----------+
## |TC |No | 26|Inf | Inf| 0.810930216|-1.4350845|
## | |Yes|503|Inf | 2.2723452|-0.043744549|-1.9436400|
## +-----------------+---+---+----+----------+------------+----------+
## |deforestation |No |494|Inf | 2.3250579| 0.048592555|-1.8870696|
## | |Yes| 35|Inf | 2.3671236|-0.780158558|-2.3671236|
## +-----------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +-----------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=2, cex.sub=1)
f3 <- lrm(risk ~ angle +building + EN + DepTaludeAterro+ DepTaludeCorte+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall_water+ wastewater+ tree + TC , data=train.data, x=TRUE , y=TRUE) stargazer(anova(f3), type=“text”, style=“default”)
# x=TRUE, y=TRUE used by resid() below
eq_OLR_03 <- polr(risk ~ wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, data=train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_03))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## woodTRUE 1.28818143 0.3280250 3.9270834 4.299108e-05
## TC_mature_soilTRUE 0.38543801 0.2204994 1.7480228 4.023004e-02
## T_constructionTRUE 0.48538416 0.2990911 1.6228640 5.230924e-02
## landfillTRUE -0.05353937 0.2924927 -0.1830452 4.273813e-01
## crackTRUE 1.83781197 0.3236920 5.6776558 6.827657e-09
## leaning_wallTRUE 2.32739513 0.5301272 4.3902579 5.660815e-06
## treeTRUE -0.05983224 0.2403399 -0.2489485 4.017003e-01
## downward_floorTRUE 0.81419597 0.3530841 2.3059548 1.055658e-02
## tiltedTRUE 1.26843267 0.3117441 4.0688263 2.362528e-05
## ground_vegTRUE 0.65395947 0.2693572 2.4278522 7.594265e-03
## scarsTRUE 3.85857762 0.3520260 10.9610574 2.940411e-28
## conc_rainfallTRUE 1.17311115 0.5605247 2.0928806 1.817991e-02
## wastewaterTRUE 0.46397067 0.2400519 1.9327930 2.663085e-02
## bananaTRUE 0.33372748 0.2470893 1.3506350 8.840619e-02
## drainage.L 0.93781055 0.2811345 3.3358072 4.252606e-04
## drainage.Q -0.17476018 0.1890862 -0.9242353 1.776819e-01
## R1|R2 0.34489485 0.5452334 0.6325637 2.635093e-01
## R2|R3 4.73301097 0.6032375 7.8460164 2.147304e-15
## R3|R4 9.76851921 0.7444785 13.1212920 1.243296e-39
stargazer((ctable), type="text", style="default", digits = 2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE 1.29 0.33 3.93 0.0000
## TC_mature_soilTRUE 0.39 0.22 1.75 0.04
## T_constructionTRUE 0.49 0.30 1.62 0.05
## landfillTRUE -0.05 0.29 -0.18 0.43
## crackTRUE 1.84 0.32 5.68 0
## leaning_wallTRUE 2.33 0.53 4.39 0.0000
## treeTRUE -0.06 0.24 -0.25 0.40
## downward_floorTRUE 0.81 0.35 2.31 0.01
## tiltedTRUE 1.27 0.31 4.07 0.0000
## ground_vegTRUE 0.65 0.27 2.43 0.01
## scarsTRUE 3.86 0.35 10.96 0
## conc_rainfallTRUE 1.17 0.56 2.09 0.02
## wastewaterTRUE 0.46 0.24 1.93 0.03
## bananaTRUE 0.33 0.25 1.35 0.09
## drainage.L 0.94 0.28 3.34 0.0004
## drainage.Q -0.17 0.19 -0.92 0.18
## R1| R2 0.34 0.55 0.63 0.26
## R2| R3 4.73 0.60 7.85 0
## R3| R4 9.77 0.74 13.12 0
## ---------------------------------------------------
#print (f3 , latex =TRUE , coefs =5)
par(mfrow=c(3,5))
plot.xmean.ordinaly (risk ~ wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage,,
data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |455|Inf | 2.2344036|-0.207332945|-2.3122939|
## | |Yes| 74|Inf | 3.1640676| 1.455287233|-0.5543107|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |258|Inf | 1.9547991|-0.202236866|-2.1465808|
## | |Yes|271|Inf | 2.8371272| 0.185027918|-1.7245072|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |204|Inf | 1.5404450|-0.996613121|-3.0757750|
## | |Yes|325|Inf | 3.3514977| 0.588744061|-1.5059589|
## +--------------+---+---+----+----------+------------+----------+
## |landfill |No |328|Inf | 1.8647846|-0.523855124|-2.4523305|
## | |Yes|201|Inf | 4.1896547| 0.878289614|-1.3312346|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |447|Inf | 2.1897896|-0.292904016|-2.5625426|
## | |Yes| 82|Inf | 3.6888795| 2.093234864|-0.2451225|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |499|Inf | 2.2635346|-0.108322227|-2.1300270|
## | |Yes| 30|Inf | Inf| 2.639057330| 0.0000000|
## +--------------+---+---+----+----------+------------+----------+
## |tree |No |209|Inf | 1.7104138|-0.601209685|-2.2460147|
## | |Yes|320|Inf | 3.0122616| 0.379489622|-1.7346011|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |466|Inf | 2.1877233|-0.267681406|-2.2116133|
## | |Yes| 63|Inf | Inf| 4.127134385|-0.6225296|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |424|Inf | 2.1062528|-0.431082272|-2.6115899|
## | |Yes|105|Inf | 4.6443909| 2.495269437|-0.5260931|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |154|Inf | 1.3781972|-1.261131218|-2.6672282|
## | |Yes|375|Inf | 3.1107337| 0.461345567|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |316|Inf | 1.7697806|-1.450832882|-4.6475909|
## | |Yes|213|Inf | 5.3565863| 3.120895417|-0.8228250|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 19|Inf |-0.3184537|-2.890371758| -Inf|
## | |Yes|510|Inf | 2.5776884| 0.062765696|-1.8718022|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.505749471|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.322516025|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |banana |No |342|Inf | 1.9129039|-0.366625275|-2.3058057|
## | |Yes|187|Inf | 4.1163235| 0.677146839|-1.3997174|
## +--------------+---+---+----+----------+------------+----------+
## |drainage |Y | 67|Inf | 0.7156200|-1.998095902|-4.1896547|
## | |P |232|Inf | 2.4168532|-0.492476485|-2.5374247|
## | |N |230|Inf | 3.6198866| 0.996829594|-1.2809338|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.6, cex.axis=0.6, cex.sub=0.6)
f4 <- lrm(risk ~ building + EN
+ DepEncNatural
+ crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + drainage + TC_mature_Soil + TC + +ground_veg
,data=train.data, x=TRUE , y=TRUE) # x=TRUE, y=TRUE used by resid() below #print (f4 , latex =TRUE , coefs =5) stargazer(anova(f4), type=“text”, style=“default”)
eq_OLR_04 <- polr(risk~ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, data= train.data
, method = "logistic", Hess = TRUE)
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- coef(summary(eq_OLR_04))
ctable <- cbind(ctable, "p value" = p )
## Warning in cbind(ctable, `p value` = p): number of rows of result is not a
## multiple of vector length (arg 2)
ctable
## Value Std. Error t value p value
## woodTRUE 1.28904486 0.3280559 3.9293456 4.299108e-05
## TC_mature_soilTRUE 0.39131811 0.2181114 1.7941207 4.023004e-02
## T_constructionTRUE 0.45322812 0.2424371 1.8694668 5.230924e-02
## crackTRUE 1.83090006 0.3213710 5.6971535 4.273813e-01
## leaning_wallTRUE 2.32773256 0.5296259 4.3950504 6.827657e-09
## treeTRUE -0.05553275 0.2391493 -0.2322095 5.660815e-06
## downward_floorTRUE 0.80482047 0.3493043 2.3040670 4.017003e-01
## tiltedTRUE 1.25834755 0.3066457 4.1035884 1.055658e-02
## ground_vegTRUE 0.65085487 0.2688644 2.4207548 2.362528e-05
## scarsTRUE 3.85994351 0.3519907 10.9660376 7.594265e-03
## conc_rainfallTRUE 1.16931455 0.5600302 2.0879490 2.940411e-28
## wastewaterTRUE 0.47142433 0.2364497 1.9937616 1.817991e-02
## bananaTRUE 0.33191296 0.2468574 1.3445532 2.663085e-02
## drainage.L 0.93412470 0.2804480 3.3308302 8.840619e-02
## drainage.Q -0.17524330 0.1890681 -0.9268791 4.252606e-04
## R1|R2 0.34576736 0.5449837 0.6344545 1.776819e-01
## R2|R3 4.73315749 0.6030061 7.8492700 2.635093e-01
## R3|R4 9.76920907 0.7442335 13.1265374 2.147304e-15
stargazer((ctable), type="text", style="default", digits=2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE 1.29 0.33 3.93 0.0000
## TC_mature_soilTRUE 0.39 0.22 1.79 0.04
## T_constructionTRUE 0.45 0.24 1.87 0.05
## crackTRUE 1.83 0.32 5.70 0.43
## leaning_wallTRUE 2.33 0.53 4.40 0
## treeTRUE -0.06 0.24 -0.23 0.0000
## downward_floorTRUE 0.80 0.35 2.30 0.40
## tiltedTRUE 1.26 0.31 4.10 0.01
## ground_vegTRUE 0.65 0.27 2.42 0.0000
## scarsTRUE 3.86 0.35 10.97 0.01
## conc_rainfallTRUE 1.17 0.56 2.09 0
## wastewaterTRUE 0.47 0.24 1.99 0.02
## bananaTRUE 0.33 0.25 1.34 0.03
## drainage.L 0.93 0.28 3.33 0.09
## drainage.Q -0.18 0.19 -0.93 0.0004
## R1| R2 0.35 0.54 0.63 0.18
## R2| R3 4.73 0.60 7.85 0.26
## R3| R4 9.77 0.74 13.13 0
## ---------------------------------------------------
par(mfrow=c(4,4))
plot.xmean.ordinaly (risk ~ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |455|Inf | 2.2344036|-0.207332945|-2.3122939|
## | |Yes| 74|Inf | 3.1640676| 1.455287233|-0.5543107|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |258|Inf | 1.9547991|-0.202236866|-2.1465808|
## | |Yes|271|Inf | 2.8371272| 0.185027918|-1.7245072|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |204|Inf | 1.5404450|-0.996613121|-3.0757750|
## | |Yes|325|Inf | 3.3514977| 0.588744061|-1.5059589|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |447|Inf | 2.1897896|-0.292904016|-2.5625426|
## | |Yes| 82|Inf | 3.6888795| 2.093234864|-0.2451225|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |499|Inf | 2.2635346|-0.108322227|-2.1300270|
## | |Yes| 30|Inf | Inf| 2.639057330| 0.0000000|
## +--------------+---+---+----+----------+------------+----------+
## |tree |No |209|Inf | 1.7104138|-0.601209685|-2.2460147|
## | |Yes|320|Inf | 3.0122616| 0.379489622|-1.7346011|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |466|Inf | 2.1877233|-0.267681406|-2.2116133|
## | |Yes| 63|Inf | Inf| 4.127134385|-0.6225296|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |424|Inf | 2.1062528|-0.431082272|-2.6115899|
## | |Yes|105|Inf | 4.6443909| 2.495269437|-0.5260931|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |154|Inf | 1.3781972|-1.261131218|-2.6672282|
## | |Yes|375|Inf | 3.1107337| 0.461345567|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |316|Inf | 1.7697806|-1.450832882|-4.6475909|
## | |Yes|213|Inf | 5.3565863| 3.120895417|-0.8228250|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 19|Inf |-0.3184537|-2.890371758| -Inf|
## | |Yes|510|Inf | 2.5776884| 0.062765696|-1.8718022|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.505749471|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.322516025|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |banana |No |342|Inf | 1.9129039|-0.366625275|-2.3058057|
## | |Yes|187|Inf | 4.1163235| 0.677146839|-1.3997174|
## +--------------+---+---+----+----------+------------+----------+
## |drainage |Y | 67|Inf | 0.7156200|-1.998095902|-4.1896547|
## | |P |232|Inf | 2.4168532|-0.492476485|-2.5374247|
## | |N |230|Inf | 3.6198866| 0.996829594|-1.2809338|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
# x=TRUE, y=TRUE used by resid() below
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")
eq_OLR_05 <- polr(risk ~ brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_05))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -0.94633319 0.4418507 -2.1417489 1.610685e-02
## woodTRUE 1.32844131 0.3262925 4.0713201 2.337373e-05
## TC_mature_soilTRUE 0.41708740 0.2151759 1.9383559 2.628991e-02
## T_constructionTRUE 0.46743526 0.2369222 1.9729482 2.425073e-02
## crackTRUE 1.77127862 0.3183722 5.5635475 1.321724e-08
## leaning_wallTRUE 2.24411392 0.5265558 4.2618733 1.013602e-05
## scarsTRUE 3.97274027 0.3533932 11.2417007 1.272164e-29
## downward_floorTRUE 0.86649559 0.3527597 2.4563338 7.018135e-03
## tiltedTRUE 1.37252008 0.3059474 4.4861306 3.626415e-06
## conc_rainfallTRUE 1.66853924 0.5243323 3.1822169 7.307617e-04
## wastewaterTRUE 0.62290661 0.2296618 2.7122780 3.341127e-03
## ground_vegTRUE 0.90000203 0.2434713 3.6965420 1.092781e-04
## R1|R2 0.07686802 0.6656727 0.1154742 4.540346e-01
## R2|R3 4.31988276 0.7196337 6.0028912 9.691726e-10
## R3|R4 9.39977784 0.8258966 11.3813014 2.591031e-30
stargazer((ctable), type="text", style="default", digits = 2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE -0.95 0.44 -2.14 0.02
## woodTRUE 1.33 0.33 4.07 0.0000
## TC_mature_soilTRUE 0.42 0.22 1.94 0.03
## T_constructionTRUE 0.47 0.24 1.97 0.02
## crackTRUE 1.77 0.32 5.56 0
## leaning_wallTRUE 2.24 0.53 4.26 0.0000
## scarsTRUE 3.97 0.35 11.24 0
## downward_floorTRUE 0.87 0.35 2.46 0.01
## tiltedTRUE 1.37 0.31 4.49 0.0000
## conc_rainfallTRUE 1.67 0.52 3.18 0.001
## wastewaterTRUE 0.62 0.23 2.71 0.003
## ground_vegTRUE 0.90 0.24 3.70 0.0001
## R1| R2 0.08 0.67 0.12 0.45
## R2| R3 4.32 0.72 6.00 0
## R3| R4 9.40 0.83 11.38 0
## ---------------------------------------------------
par(mfrow=c(3,4))
plot.xmean.ordinaly (risk ~ brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |brick |No | 38|Inf | 2.8903718| 1.673976434|-0.4274440|
## | |Yes|491|Inf | 2.2936565|-0.110090690|-2.1119270|
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |455|Inf | 2.2344036|-0.207332945|-2.3122939|
## | |Yes| 74|Inf | 3.1640676| 1.455287233|-0.5543107|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |258|Inf | 1.9547991|-0.202236866|-2.1465808|
## | |Yes|271|Inf | 2.8371272| 0.185027918|-1.7245072|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |204|Inf | 1.5404450|-0.996613121|-3.0757750|
## | |Yes|325|Inf | 3.3514977| 0.588744061|-1.5059589|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |447|Inf | 2.1897896|-0.292904016|-2.5625426|
## | |Yes| 82|Inf | 3.6888795| 2.093234864|-0.2451225|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |499|Inf | 2.2635346|-0.108322227|-2.1300270|
## | |Yes| 30|Inf | Inf| 2.639057330| 0.0000000|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |316|Inf | 1.7697806|-1.450832882|-4.6475909|
## | |Yes|213|Inf | 5.3565863| 3.120895417|-0.8228250|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |466|Inf | 2.1877233|-0.267681406|-2.2116133|
## | |Yes| 63|Inf | Inf| 4.127134385|-0.6225296|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |424|Inf | 2.1062528|-0.431082272|-2.6115899|
## | |Yes|105|Inf | 4.6443909| 2.495269437|-0.5260931|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 19|Inf |-0.3184537|-2.890371758| -Inf|
## | |Yes|510|Inf | 2.5776884| 0.062765696|-1.8718022|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.505749471|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.322516025|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |154|Inf | 1.3781972|-1.261131218|-2.6672282|
## | |Yes|375|Inf | 3.1107337| 0.461345567|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
# x=TRUE, y=TRUE used by resid() below
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")
eq_OLR_06 <- polr(risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_06))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -1.18019664 0.5346808 -2.2072921 1.364683e-02
## woodTRUE 1.16496612 0.3360451 3.4666954 2.634493e-04
## mixedTRUE 0.10829211 0.5229322 0.2070863 4.179712e-01
## ENTRUE 0.88184759 0.3946729 2.2343759 1.272918e-02
## TCTRUE 0.72915922 0.5190235 1.4048674 8.003035e-02
## T_constructionTRUE 0.26513259 0.3556993 0.7453842 2.280198e-01
## landfillTRUE 0.16242865 0.3156518 0.5145817 3.034227e-01
## leakTRUE 0.03822058 0.2331227 0.1639505 4.348851e-01
## garbageTRUE 0.23317558 0.2896901 0.8049139 2.104347e-01
## crackTRUE 1.76180463 0.3283290 5.3659726 4.025708e-08
## leaning_wallTRUE 2.35218395 0.5361686 4.3870232 5.745627e-06
## treeTRUE -0.06300889 0.2428688 -0.2594359 3.976495e-01
## tiltedTRUE 1.37759653 0.3131828 4.3986978 5.445116e-06
## angleD 0.07871442 0.4866540 0.1617462 4.357529e-01
## angleE 0.54025202 0.5546598 0.9740240 1.650223e-01
## ground_vegTRUE 0.80974449 0.2646215 3.0600105 1.106646e-03
## scarsTRUE 3.99537267 0.3547774 11.2616311 1.014833e-29
## conc_rainfallTRUE 1.79047230 0.5284973 3.3878549 3.522076e-04
## wastewaterTRUE 0.59574614 0.2347552 2.5377330 5.578653e-03
## bananaTRUE 0.30350978 0.2547587 1.1913620 1.167558e-01
## R1|R2 1.07788542 1.0897206 0.9891392 1.612975e-01
## R2|R3 5.33027409 1.1260264 4.7337024 1.102304e-06
## R3|R4 10.39993583 1.2140931 8.5660116 5.356556e-18
stargazer((ctable), type="text", style="default", digits = 2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE -1.18 0.53 -2.21 0.01
## woodTRUE 1.16 0.34 3.47 0.0003
## mixedTRUE 0.11 0.52 0.21 0.42
## ENTRUE 0.88 0.39 2.23 0.01
## TCTRUE 0.73 0.52 1.40 0.08
## T_constructionTRUE 0.27 0.36 0.75 0.23
## landfillTRUE 0.16 0.32 0.51 0.30
## leakTRUE 0.04 0.23 0.16 0.43
## garbageTRUE 0.23 0.29 0.80 0.21
## crackTRUE 1.76 0.33 5.37 0.0000
## leaning_wallTRUE 2.35 0.54 4.39 0.0000
## treeTRUE -0.06 0.24 -0.26 0.40
## tiltedTRUE 1.38 0.31 4.40 0.0000
## angleD 0.08 0.49 0.16 0.44
## angleE 0.54 0.55 0.97 0.17
## ground_vegTRUE 0.81 0.26 3.06 0.001
## scarsTRUE 4.00 0.35 11.26 0
## conc_rainfallTRUE 1.79 0.53 3.39 0.0004
## wastewaterTRUE 0.60 0.23 2.54 0.01
## bananaTRUE 0.30 0.25 1.19 0.12
## R1| R2 1.08 1.09 0.99 0.16
## R2| R3 5.33 1.13 4.73 0.0000
## R3| R4 10.40 1.21 8.57 0
## ---------------------------------------------------
par(mfrow=c(5,4))
plot.xmean.ordinaly (risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |brick |No | 38|Inf | 2.8903718| 1.673976434|-0.4274440|
## | |Yes|491|Inf | 2.2936565|-0.110090690|-2.1119270|
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |455|Inf | 2.2344036|-0.207332945|-2.3122939|
## | |Yes| 74|Inf | 3.1640676| 1.455287233|-0.5543107|
## +--------------+---+---+----+----------+------------+----------+
## |mixed |No |491|Inf | 2.2936565|-0.077431740|-2.0299933|
## | |Yes| 38|Inf | 2.8903718| 1.029619417|-0.8979416|
## +--------------+---+---+----+----------+------------+----------+
## |EN |No |339|Inf | 1.8769173|-0.499827870|-2.3321439|
## | |Yes|190|Inf | 4.5432948| 0.923670839|-1.3862944|
## +--------------+---+---+----+----------+------------+----------+
## |TC |No | 26|Inf | Inf| 0.810930216|-1.4350845|
## | |Yes|503|Inf | 2.2723452|-0.043744549|-1.9436400|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |204|Inf | 1.5404450|-0.996613121|-3.0757750|
## | |Yes|325|Inf | 3.3514977| 0.588744061|-1.5059589|
## +--------------+---+---+----+----------+------------+----------+
## |landfill |No |328|Inf | 1.8647846|-0.523855124|-2.4523305|
## | |Yes|201|Inf | 4.1896547| 0.878289614|-1.3312346|
## +--------------+---+---+----+----------+------------+----------+
## |leak |No |332|Inf | 1.9322113|-0.390427231|-2.3848232|
## | |Yes|197|Inf | 3.6480575| 0.662841831|-1.3673664|
## +--------------+---+---+----+----------+------------+----------+
## |garbage |No |346|Inf | 2.0632861|-0.279257423|-2.4298469|
## | |Yes|183|Inf | 3.0853444| 0.525424423|-1.2739652|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |447|Inf | 2.1897896|-0.292904016|-2.5625426|
## | |Yes| 82|Inf | 3.6888795| 2.093234864|-0.2451225|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |499|Inf | 2.2635346|-0.108322227|-2.1300270|
## | |Yes| 30|Inf | Inf| 2.639057330| 0.0000000|
## +--------------+---+---+----+----------+------------+----------+
## |tree |No |209|Inf | 1.7104138|-0.601209685|-2.2460147|
## | |Yes|320|Inf | 3.0122616| 0.379489622|-1.7346011|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |424|Inf | 2.1062528|-0.431082272|-2.6115899|
## | |Yes|105|Inf | 4.6443909| 2.495269437|-0.5260931|
## +--------------+---+---+----+----------+------------+----------+
## |angle |C | 29|Inf | Inf|-0.068992871|-3.3322045|
## | |D |128|Inf | 3.4339872| 0.899941594|-1.3192837|
## | |E |372|Inf | 2.0348576|-0.292387963|-2.1162555|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |154|Inf | 1.3781972|-1.261131218|-2.6672282|
## | |Yes|375|Inf | 3.1107337| 0.461345567|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |316|Inf | 1.7697806|-1.450832882|-4.6475909|
## | |Yes|213|Inf | 5.3565863| 3.120895417|-0.8228250|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 19|Inf |-0.3184537|-2.890371758| -Inf|
## | |Yes|510|Inf | 2.5776884| 0.062765696|-1.8718022|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.505749471|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.322516025|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |banana |No |342|Inf | 1.9129039|-0.366625275|-2.3058057|
## | |Yes|187|Inf | 4.1163235| 0.677146839|-1.3997174|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
predictedLevel1 <- predict(eq_OLR_01, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_01, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel1)
## predictedLevel1
## R1 R2 R3 R4
## R1 3 16 0 0
## R2 1 86 6 0
## R3 0 25 50 9
## R4 0 0 17 11
p1 <- mean(as.character(test.data$risk) != as.character(predictedLevel1)) #misclassification error
p1
## [1] 0.3303571
predictedLevel2 <- predict(eq_OLR_02, test.data) # predict the levels directly
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel2)
## predictedLevel2
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 2 85 6 0
## R3 0 23 51 10
## R4 0 0 16 12
p2 <- mean(as.character(test.data$risk) != as.character(predictedLevel2))
p2
## [1] 0.3214286
predictedLevel3 <- predict(eq_OLR_03, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_03, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel3)
## predictedLevel3
## R1 R2 R3 R4
## R1 3 16 0 0
## R2 2 86 5 0
## R3 0 25 50 9
## R4 0 0 15 13
p3 <- mean(as.character(test.data$risk) != as.character(predictedLevel3))
p3
## [1] 0.3214286
predictedLevel4 <- predict(eq_OLR_04, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_04, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel4)
## predictedLevel4
## R1 R2 R3 R4
## R1 3 16 0 0
## R2 2 86 5 0
## R3 0 25 50 9
## R4 0 0 15 13
p4 <- mean(as.character(test.data$risk) != as.character(predictedLevel4))
p4
## [1] 0.3214286
predictedLevel5 <- predict(eq_OLR_05, test.data) # predict the levels directly
predictedScores5 <- predict(eq_OLR_05, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel5)
## predictedLevel5
## R1 R2 R3 R4
## R1 3 16 0 0
## R2 2 84 7 0
## R3 0 24 51 9
## R4 0 0 15 13
p5 <- mean(as.character(test.data$risk) != as.character(predictedLevel5))
p5
## [1] 0.3258929
predictedLevel6 <- predict(eq_OLR_06, test.data) # predict the levels directly
predictedScores6 <- predict(eq_OLR_06, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel6)
## predictedLevel6
## R1 R2 R3 R4
## R1 2 17 0 0
## R2 1 86 6 0
## R3 0 25 50 9
## R4 0 0 17 11
p6 <- mean(as.character(test.data$risk) != as.character(predictedLevel6))
p6
## [1] 0.3348214
#Table
df2 <- data.frame(
"Equations"=c(1:6),
"Predicted"=c(1-p1,
1-p2,
1-p3,
1-p4,
1-p5,
1-p6
)
)
df2
## Equations Predicted
## 1 1 0.6696429
## 2 2 0.6785714
## 3 3 0.6785714
## 4 4 0.6785714
## 5 5 0.6741071
## 6 6 0.6651786